Robotic Forklift for Stacking Multiple Pallets with RGB-D Cameras

Abstract

We propose a robotic forklift system for stacking mul¬tiple mesh pallets. The stacking of mesh pallets is an essential task for the shipping and storage of loads. However, stacking, the placement of pallet feet on pal-let edges, is a complex problem owing to the small sizes of the feet and edges, leading to a complexity in the detection and the need for high accuracy in adjusting the pallets. To detect the pallets accurately, we uti¬lize multiple RGB-D (RGB Depth) cameras that pro¬duce dense depth data under the limitations of the sen¬sor position. However, the depth data contain noise. Hence, we implement a region growing-based algo¬rithm to extract the pallet feet and edges without re¬moving them. In addition, we design the control law based on path following control for the forklift to ad¬just the position and orientation of two pallets. To evaluate the performance of the proposed system, we conducted an experiment assuming a real task. The experimental results demonstrated that the proposed system can achieve a stacking operation with a real forklift and mesh pallets.